دورية أكاديمية

The roles of IRF8 in nonspecific orbital inflammation: an integrated analysis by bioinformatics and machine learning

التفاصيل البيبلوغرافية
العنوان: The roles of IRF8 in nonspecific orbital inflammation: an integrated analysis by bioinformatics and machine learning
المؤلفون: Zixuan Wu, Jinfeng Xu, Yi Hu, Xin Peng, Zheyuan Zhang, Xiaolei Yao, Qinghua Peng
المصدر: Journal of Ophthalmic Inflammation and Infection, Vol 14, Iss 1, Pp 1-19 (2024)
بيانات النشر: SpringerOpen, 2024.
سنة النشر: 2024
المجموعة: LCC:Ophthalmology
مصطلحات موضوعية: Nonspecific orbital inflammation (NSOI), IRF8, Lasso regression, SVM-RFE, Autoimmune inflammatory disorder, Ophthalmology, RE1-994
الوصف: Abstract Background Nonspecific Orbital Inflammation (NSOI) represents a persistent and idiopathic proliferative inflammatory disorder, characterized by polymorphous lymphoid infiltration within the orbit. The transcription factor Interferon Regulatory Factor 8 (IRF8), integral to the IRF protein family, was initially identified as a pivotal element for the commitment and differentiation of myeloid cell lineage. Serving as a central regulator of innate immune receptor signaling, IRF8 orchestrates a myriad of functions in hematopoietic cell development. However, the intricate mechanisms underlying IRF8 production remain to be elucidated, and its potential role as a biomarker for NSOI is yet to be resolved. Methods IRF8 was extracted from the intersection analysis of common DEGs of GSE58331 and GSE105149 from the GEO and immune- related gene lists in the ImmPort database using The Lasso regression and SVM-RFE analysis. We performed GSEA and GSVA with gene sets coexpressed with IRF8, and observed that gene sets positively related to IRF8 were enriched in immune-related pathways. To further explore the correlation between IRF8 and immune-related biological process, the CIBERSORT algorithm and ESTIMATE method were employed to evaluate TME characteristics of each sample and confirmed that high IRF8 expression might give rise to high immune cell infiltration. Finally, the GSE58331 was utilized to confirm the levels of expression of IRF8. Results Among the 314 differentially expressed genes (DEGs), some DEGs were found to be significantly different. With LASSO and SVM-RFE algorithms, we obtained 15 hub genes. For biological function analysis in IRF8, leukocyte mediated immunity, leukocyte cell-cell adhesion, negative regulation of immune system process were emphasized. B cells naive, Macrophages M0, Macrophages M1, T cells CD4 memory activated, T cells CD4 memory resting, T cells CD4 naive, and T cells gamma delta were shown to be positively associated with IRF8. While, Mast cells resting, Monocytes, NK cells activated, Plasma cells, T cells CD8, and T cells regulatory (Tregs) were shown to be negatively linked with IRF8. The diagnostic ability of the IRF8 in differentiating NSOI exhibited a good value. Conclusions This study discovered IRF8 that are linked to NSOI. IRF8 shed light on potential new biomarkers for NSOI and tracking its progression.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1869-5760
Relation: https://doaj.org/toc/1869-5760
DOI: 10.1186/s12348-024-00410-4
URL الوصول: https://doaj.org/article/94e09ffa6146402d9e003b40a33c3b80
رقم الأكسشن: edsdoj.94e09ffa6146402d9e003b40a33c3b80
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:18695760
DOI:10.1186/s12348-024-00410-4